The kinematic structure of closed chain mechanisms is suitable for putting an excess number of inputs in addition to the required number to control their position and orientation. With the addition of these excess inputs, it is possible to generate and control the internal forces within the mechanisms by simultaneously activating joints whose action opposes each other. The internal forces balance inside the structure of mechanisms and do not create any resultant force. However, at the static or quasi-static cases they change the stiffness of the mechanisms. In dynamic cases, in addition to the change in stiffness, they may also generate a damping effect. As a result of these effects, the dynamic behavior of closed chain mechanisms changes. This study analyzes the dynamics of the closed chain mechanisms under the effect of internal forces through the simulation and experimental results using a planar closed chain mechanism.

This paper discusses a novel design for a rotary differential NiTi shape memory alloy actuator, which incorporates a mobile heat sink. The new mechanism is described in detail, and its performance in a position control system is compared with that of the same actuator without heat sink. Experimental results are presented which show an improvement in actuator response time, as well as closed-loop bandwidth. The design of the mechanism gives enhanced performance, without the increased power consumption associated with fixed heat sinks.

The problem of path planning for a mobile robot has been studied extensively in recent literature. Much of the work in this area is devoted to the study of path planning for an earth-bound robot in two dimensions. In this paper, we explore the problem for a robot that can fly in three dimensional space or crawl on 3D surfaces or use a combination of both. We assume that the obstacles can be modeled as polyhedral objects.

Motion Planning and control of mobile vehicles with nonholonomic constraints are in their infancy. A systematic approach for modeling and base; motion control of a mobile vehicle is presented. A nonlinear coordinate transformation that takes into account the complete dynamics with nonholonomic constraints is used in order to obtain a linear system in space coordinates. An input-output feedback linearization inner loop is subsequently designed to transform this system into a linear-point mass system in the coordinates corresponding to the control objectives. A rigorous yet simple approach to motion planning through optimization techniques is presented for these mobile vehicles. The resulting Cartesian trajectory generated from the motion planning algorithm is employed as the reference trajectory in the outer loop, which is designed based on a Lyapunov function candidate. The net result is a base motion controller that gives capabilities to these mobile vehicles not only for tracking a Cartesian trajectory but also to achieve a desired final orientation (docking angle).

The use of a two-arm robot for assembling two objects, with each being held by one arm, is presented. The assembly task is decomposed into an approach phase and an assembly phase. For each phase, we propose a solution for describing the task. For the approach phase, we suggest to describe the task with respect to a mobile reference frame, attached to the end effector of one of the arms. This allows us to take advantage of the redundancy of the system. For the assembly phase, we propose two solutions, both involving some kind of force control. The first one is based upon a position control similar to the one used for the approach phase, with an updating of the reference position through a measurement of the contact forces. The second scheme is derived from a symmetrical hybrid control scheme initially proposed by Uchiyama and Dauchez to control a two-arm robot handling a single rigid object. The main results of this scheme are summarized, and the way of using it for an assembly task is presented. Finally, the experimental setup we have installed to validate our theoretical results is described.

The paper presents a geometric method for collision-free manipulator path planning in 3D Euclidean space with polyhedral obstacles. It ensures that none of the links nor the manipulator tip collide with the objects. The method is computationally very cheap and it does not require intensive off-line preprocessing. Hence, it is real-time applicable if the information about obstacles positions and shapes is obtained from a higher control level. The trajectories generated lie within the reachable workspace. The method is implemented on a VAX 11/750 computer and the simulation results are included.

This is a preliminary study to provide useful information for the design of the control of a monocycle which is one of the intelligent movable robots. In this paper, the two-degree-of-freedom monocycle is modeled by an inverted pendulum with a controlling arm pivoted at its upper end. The controlling arm is rotated to give the pendulum restoring moment.

The feedback control systems for the model have been designed using two methods – the pole assignment and the optimal control, respectively. Simulations of the control systems designed with the above methods are carried out on a personal computer. Although the pendulum can be stabilized with either of these methods, it is found that the optimal control method is superior to the pole assignment one, because in the former the control system can be designed to be suitably corresponding to the design demands based on a definite criterion.

This paper presents a sensory gripper, consisting of two tactile sensing matrices which acquire three dimensional images of objects of interest. The image processing algorithm uses elastostatic contact information to discriminate among a host of parts made of different materials. The algorithm also enables the assessment of orientation of parts without the pre-requisite of having to recognise them. The positions of stable holdsites and a safe gripping force are also evaluated.

The combination of robotics and medical imaging may soon provide orthopaedic surgeons with a tool that significantly increases the precision of cementless total hip replacement operations and directly links preoperative planning with surgical execution. Twenty-six successful robot-assisted operations have been performed on dogs and the first clinical trials on human patients have recently taken place.

The problem of incremental terrain acquisition is addressed in this paper. Through a systematic planning of movements in an unknown terrain filled with polygonal obstacles, a sensor-based robot is shown to be able to incrementally build the entire terrain model; the model will be described in terms of visibility graph and visibility window. The terrain model is built area by area without any overlapping between explored areas. As a consequence, the terrain is obtained as a tessellation of disjoint star polygons. And the adjacency relations between star polygons are represented by a star polygon adjacency graph (SPAG graph). The incremental exploration process consists of two basic tasks: local exploration and exploration merging. Useful lemmas are derived for these two tasks and, then, the algorithms for the tasks are given. Examples are used to illustrate the algorithms. Two strategies for planning robot movements in the unknown terrain environment are suggested and compared. They are the depth-first search and the breadth-first search applied to the SPAG graph. Finally, the performance evaluation of the method and comparison with some existing methods are presented.